Overview of the dataset

Gene number: representing the gene numbers in the activate assay.

Reductions: representing the dimension reduction methods conducted in this dataset.

pp.Score (Q2) : representing the median expression value of enzymolysis induced gene set (ppDEGs).

ppGroups in terms of Q2 : calculating the median of pp.Score in each cell group, then to figure out which clusters have higher pp.Scores than the pp.Score (Q2).

pp.Score (Q3) : representing The third quartile(Q3), also known as the higher quartile, is equal to the 75% of all the values in the sample arranged from the smallest to the largest of enzymolysis induced gene set (ppDEGs).

ppGroups in terms of Q3 : calculating the median of pp.Score in each cell group, then to figure out which clusters have higher pp.Scores than the pp.Score (Q3).

Overlap between ppDEGs and HVGs

In this dataset, we totally have 3000 highly variable genes (HVGs), and the number of ppDEGs is 332. The intersection between this two set were 156 (genes), which means that 46.99% ppDEGs belong to HVGs. While these HVGs will be used for PCA analysis following up.

The extent of ppEffects in each cell

In this panel, your can see the distribution of ppEffects in each cells by UMAP plot. The darker the cell color, the more severely it is affected by enzymatic hydrolysis

Groups affected by ppEffect

In this panel, we use the violin plot to display which groups were highly affected by ppEffect.

The red dotted line presented the median expression value of enzymolysis induced gene set (ppDEGs). The median expression value of ppDEGs (pp.Score Q2) in this datasets is 0.1016795 .

The yellow dotted line presented the higher quartile expression value of enzymolysis induced gene set (ppDEGs). The higher quartile expression value of ppDEGs (pp.Score Q3) in this datasets is 0.2449448 .

In this panel, we use the Dotplot to display which groups were highly affected by ppEffect.

Overlap between ppDEGs and cluster markers